Load the data

library(tidyverse)
## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ──
## ✔ ggplot2 3.4.0     ✔ purrr   1.0.1
## ✔ tibble  3.1.8     ✔ dplyr   1.1.0
## ✔ tidyr   1.3.0     ✔ stringr 1.5.0
## ✔ readr   2.1.3     ✔ forcats 1.0.0
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
bike_sharing <- read_csv("~/Downloads/bikesharing.csv")
## Rows: 731 Columns: 15
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (4): season, month, weekday, weather
## dbl  (7): year, temperature_F, casual, registered, count, humidity, windspeed
## lgl  (2): holiday, workingday
## date (2): date, date_noyear
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
bike_sharing %>%
  mutate(new_col = count/temperature_F) %>%
  ggplot(aes(date, new_col)) +
  geom_point()

bike_sharing %>%
  ggplot(aes(weather, fill=weekday)) +
  geom_bar(position="dodge")

bike_sharing %>%
  ggplot(aes(weekday, fill=weather)) +
  geom_bar(position="dodge")

Vignette 4

bike_sharing %>%
  ggplot(aes(temperature_F)) +
  geom_histogram(fill="dodgerblue")
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  ggplot(aes(temperature_F, fill=season)) +
  geom_histogram()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  ggplot(aes(temperature_F, fill=season)) +
  geom_histogram() +
  facet_wrap(~season)
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  ggplot(aes(temperature_F, fill=season)) +
  geom_histogram() +
  geom_freqpoly() +
  facet_wrap(~season)
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  ggplot(aes(temperature_F, color=season)) +
  geom_freqpoly()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  filter(season == "winter" | season == "summer") %>%
  ggplot(aes(temperature_F, color=season)) +
  geom_freqpoly()
## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

bike_sharing %>%
  filter(season == "winter" | season == "summer") %>%
  ggplot(aes(temperature_F, color=season)) +
  geom_density()

bike_sharing %>%
  ggplot(aes(temperature_F, color=season)) +
  geom_density()

bike_sharing %>%
  ggplot(aes(temperature_F, color=season)) +
  geom_density() +
  labs(title = "Temperature by season")

Vignette 5

bike_sharing %>% 
  ggplot(aes(season, humidity)) +
  geom_point(color = "dodgerblue")

bike_sharing %>% 
  ggplot(aes(season, humidity)) +
  geom_jitter(color = "dodgerblue")

bike_sharing %>% 
  ggplot(aes(season, humidity)) +
  geom_boxplot()

bike_sharing %>% 
  ggplot(aes(season, humidity)) +
  geom_jitter() +
  geom_boxplot() 

bike_sharing %>% 
  ggplot(aes(season, humidity, fill=weather)) +
  geom_boxplot()

## Vignette 6

bike_sharing %>%
  ggplot(aes(date, count)) +
  geom_point()

bike_sharing %>%
  ggplot(aes(date_noyear, count)) +
  geom_point()

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year)) +
  geom_point()

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year)) +
  geom_line()

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year, group=year)) +
  geom_line()

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year, group=year)) +
  geom_line() +
  geom_point()

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year, group=year)) +
  geom_line() +
  geom_smooth()
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

bike_sharing %>%
  ggplot(aes(date_noyear, count, color=year, group=year)) +
  geom_line() +
  geom_smooth() +
  labs(title="number of riders by date", y = "number of riders", x = "date")
## `geom_smooth()` using method = 'loess' and formula = 'y ~ x'

Vignette 7

starwars %>%
  ggplot(aes(homeworld)) +
  geom_bar(fill="dodgerblue")

starwars %>%
  group_by(homeworld) %>%
  summarize(count=n()) %>%
  filter(count > 1) %>%
  ggplot(aes(count, homeworld)) +
  geom_bar(stat = "identity", fill="dodgerblue")

starwars %>%
  drop_na(homeworld) %>%
  group_by(homeworld) %>%
  summarize(count=n()) %>%
  filter(count > 1) %>%
  ggplot(aes(count, homeworld)) +
  geom_bar(stat = "identity", fill="dodgerblue")

starwars %>%
  drop_na(homeworld) %>%
  group_by(homeworld) %>%
  summarize(count=n()) %>%
  filter(count > 1) %>%
  ggplot(aes(count, reorder(homeworld, count))) +
  geom_bar(stat = "identity", fill="dodgerblue") +
  labs(title="Frequency of homeworld in Star Wars", y = "homeworld")

starwars %>%
  ggplot(aes(species)) +
  geom_bar()

starwars %>%
  group_by(species) %>%
  summarize(count = n()) %>%
  ggplot(aes(species, count)) +
  geom_bar(stat="identity")

starwars %>%
  group_by(species) %>%
  summarize(count = n()) %>%
  filter(count > 1) %>%
  ggplot(aes(species, count)) +
  geom_bar(stat="identity")

starwars %>%
  group_by(species) %>%
  summarize(count = n()) %>%
  filter(count > 1) %>%
  ggplot(aes(count, species)) +
  geom_bar(stat="identity")

starwars %>%
  drop_na(homeworld) %>%
  drop_na(species) %>%
  group_by(species) %>%
  summarize(count = n()) %>%
  filter(count > 1) %>%
  ggplot(aes(count, reorder(species, count))) +
  geom_bar(stat="identity")